A suite of programs aimed at producing temporal series based on the observational dataset. Daily data of precipitation, maximum temperature and minimum temperature are produced. Two different algorithms have been developed: 1) generation of single point weather data series. 2) generation of a spatially coherent two-dimensional data series.
PRAGA PRogram for AGrometeorological Analysis
MeteoInfo: GIS, scientific computation and visualization environment.
🌊 A lightweight wave buoy for near-shore deployments.
Deep data introspection for the National Solar Radiation Database
Massive-Parallel Trajectory Calculations (MPTRAC) is a Lagrangian particle dispersion model for the analysis of atmospheric transport processes in the free troposphere and stratosphere.
MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.
IMPROVER is a library of algorithms for meteorological post-processing.
🐍 + 🌊 A python framework for working with met-ocean data
Load and create NetCDF files in Julia
DWD Global Radiation Observation and Forecast Data Library - a Python package providing access to Surface Incoming Solar Radiation (SIS) or Global Horizontal Irradiance (GHI) data from Deutscher Wetterdienst (DWD). Covers Germany, Austria, and Switzerland. Useful for photovoltaic systems and Smart Home scenarios.
Command-line utilities and fortran modules for meteorological data processing
A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
🌍 A Collection of Awesome Large Weather Models (LWMs) | AI for Earth (AI4Earth) | AI for Science (AI4Science)
Open weather data for humans.
The new version of the INAMHI GEOGLOWS portal, developed using Angular, Django, and Docker for enhanced scalability and performance.
Decode CINRAD (China New Generation Weather Radar) data and visualize.
Efficiently, easily, and rapidly download the latest Multi-Radar Multi-Sensor (MRMS) data
Repositorio del proyecto de homogenización de series de Tiempo de Precipitación. Este trabajo se enmarca en la realización del trabajo fin de master del estudiante Nicolas Maldonado del Master en Ciencia de Datos de la Universidad de la Rioja, realizando la automatización de una guia desarrollada por la U. Distrital Francisco Jose de Caldas
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